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A sample for which the respondents themselves decide whether to be included.

Context

Description of what the values represent.

Source

The researchers geting all the data.

Sampling Method

The samples that you choose to use to collect sample data. Example: Voluntary response sample

Conclusions

Making statements that are clear to those without any understanding of statistics and its terminology.

Pratical Implications

A practical conclusion. A statement that could be true.

Statistical Significance

a statistical assessment of whether observations show a pattern rather than being just a chance.

Practical Significance

a limit where an observed difference is of some practical use in the real world

Parameter Vs. Statistic

Parameter: numerical measurement describing some characteristic of a population. Statistic: numerical measuremetn describing some characteristic of a sample.

Quantitative Vs. Categorical

Quantitative data: consiste of numbers representing counts or measurements. Categorical data: consists of names or labels that are not numbers representing counts or measurements.

Discrete Vs. Continuous

Discrete data result when the number of possible valuse is either a finite number or a "countable" number. Continuous data result from infinitely many possible values that correspond to some continuous scale that covers a range of values without gaps,

Levels of Measurements

Ratio, interval, Nominal, Ordinal

Nominal

Categories only. Data cannot be arranged in an ordering scheme.

Ordinal

Categories are ordered, but differences can't be found or are meaningless.

interval

Differences are meaningful, but there is no natural zero starting point and ratios are meaningless